Keepa Product Time-Series Data Explorer

This skill guides you on how to query and analyze Amazon product historical time-series data, helping Amazon sellers track price movements, BSR trends, rating changes, and other key product metrics over time.

Core Concepts

This tool provides historical time-series data for individual Amazon products (ASINs) powered by Keepa. It returns timestamped data points for various metrics, allowing trend analysis over a configurable time window (up to 365 days). Each query targets a single ASIN in a specific Amazon marketplace.

Time-series format: All data series are returned as arrays of {time, value} objects, where time is a timestamp and value is the metric at that point. BSR data includes a categoryName field along with a points array.

BSR logic: A smaller BSR value means a better sales rank. Rank 1 is the top-selling product in its category. When a user says "BSR improved", it means the numeric value decreased; "BSR dropped" means the value increased.

Available Data Series

Supported Marketplaces

Default marketplace is 1 (US). Use domain=1 when the user does not specify a marketplace.

API Usage

This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/keepa_product_history.py directly to run queries.

Parameter Guide

Required Parameters

• asin: The Amazon Standard Identification Number to query. Only a single ASIN per request is supported.
• domain: The Amazon marketplace domain ID (see table above). Always map the user's marketplace mention to the correct numeric ID.

Optional Parameters

• days: Number of historical days to retrieve (1-365, default 90). Use 30 for short-term, 90 for medium-term, 365 for long-term analysis.
• show* flags: Set any show* parameter to 1 to include that data series. By default, only the core series (Buy Box price, rating, rating count, monthly sales, sub-category BSR) are returned.

How to Choose Parameters

1. Price analysis: Enable showPrice, showPriceList, showPriceDeal, showPriceCoupon as needed for the specific price comparison the user wants.
2. FBA vs FBM comparison: Enable both showPriceFba and showPriceFbm.
3. BSR deep-dive: Enable showBsrMain to get the root category BSR alongside the always-returned sub-category BSR.
4. Competitive landscape: Enable showSellerCount to see how many sellers are competing.
5. Full product overview: Enable all show flags for a comprehensive historical snapshot.

Usage Examples

1. Basic price history for a US product

asin: B0XXXXXXXX, domain: 1, days: 90

2. Long-term BSR trend (1 year) on the German marketplace

asin: B0XXXXXXXX, domain: 3, days: 365, showBsrMain: 1

3. Price comparison across fulfillment channels

asin: B0XXXXXXXX, domain: 1, days: 30, showPriceFba: 1, showPriceFbm: 1, showPrice: 1

4. Deal and coupon price tracking

asin: B0XXXXXXXX, domain: 1, days: 90, showPriceDeal: 1, showPriceCoupon: 1

5. Full product health check

asin: B0XXXXXXXX, domain: 1, days: 90, showPrice: 1, showPriceList: 1, showPriceDeal: 1, showPricePrime: 1, showPriceFba: 1, showPriceFbm: 1, showPriceCoupon: 1, showBsrMain: 1, showSellerCount: 1

Display Rules

1. Present data clearly: Show time-series data in tables or describe trends; avoid subjective business advice unless the user explicitly asks for it.
2. BSR clarification: When showing BSR data, remind users that lower values mean better (higher) sales ranks.
3. Price formatting: Display prices with proper currency symbols matching the marketplace ($ for US, EUR for DE/FR/ES/IT, GBP for UK, JPY for JP, etc.).
4. Time formatting: Present timestamps in a human-readable date format.
5. Trend summarization: When data series are long, summarize the overall trend (e.g., "price decreased from $29.99 to $24.99 over 90 days") and highlight significant changes such as price drops, BSR spikes, or rating shifts.
6. Error handling: When a query fails, explain the reason and suggest corrections (e.g., verify the ASIN is valid, check the marketplace domain ID).
7. Single ASIN limitation: If the user asks about multiple ASINs, inform them that queries must be made one ASIN at a time, and run multiple sequential calls.

Important Limitations

• Single ASIN per query: Only one ASIN can be queried at a time. For multi-ASIN comparisons, make separate requests.
• Maximum 365 days: Historical data is limited to at most 365 days back.
• Data granularity: Data points are at irregular intervals depending on when Keepa captured changes, not at fixed daily intervals.

User Expression & Scenario Quick Reference

Applicable -- Historical product-level data queries on Amazon:

Not applicable -- Needs beyond product-level historical data:

• Search term / keyword analysis (use ABA data instead)
• Advertising / PPC campaign data
• Listing copywriting or content optimization
• Category-wide or market-level aggregate trends (this tool is per-ASIN only)
• Real-time inventory or stock level checks
• Product reviews text or sentiment analysis

Boundary judgment: When users say "product research" or "competitor analysis", if it boils down to examining a specific ASIN's historical price, BSR, or sales data, this skill applies. If they need keyword data, market-wide trends, or advertising metrics, it does not apply.

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply:

1. The functionality or purpose described in this skill does not match actual behavior
2. The skill's results do not match the user's intent
3. The user expresses dissatisfaction or praise about this skill
4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

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